Evidence map›Paper›PMID 38850243›Full record

ArticleACS applied materials & interfaces2024

Minimizing Contact Resistance and Flicker Noise in Micro Graphene Hall Sensors Using Persistent Carbene Modified Gold Electrodes.

Honglin Sun, Ting Huang, Md Masruck Alam, Jingwei Li, Dong Wook Jang, Tianle Wang, Haohan Chen, Yi-Ping Ho, Zhaoli Gao

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Article in ACS applied materials & interfaces, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Honglin SunDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Ting HuangDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Md Masruck AlamDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Jingwei LiDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Dong Wook JangDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Tianle WangDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Haohan ChenDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.
Yi-Ping HoDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.ORCID 0000-0002-2052-9724
Zhaoli GaoDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, New Territories 999077, Hong Kong SAR, China.ORCID 0000-0003-3114-2207

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scalable micro graphene Hall sensors (μGHSs) hold tremendous potential for highly sensitive and label-free biomagnetic sensing in physiological solutions. To enhance the performance of these devices, it is crucial to optimize frequency-dependent flicker noise to reduce the limit of detection (LOD), but it remains a great challenge due to the large contact resistance at the graphene-metal contact. Here we present a surface modification strategy employing persistent carbene on gold electrodes to reduce the contact resistivity by a factor of 25, greatly diminishing μGHS flicker noise by a factor of 1000 to 3.13 × 10

Indexed as

2D MaterialsContact NoiseGrapheneMagnetic SensingMicro Hall Sensor

Identifiers

PMID38850243
PMCPMC11194764

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.